In yangjl/quantgen: R package for basic quantgen simulation and/or modeling.

knitr::opts_chunk$set(echo = TRUE)

Short-term Results

Variability of the responses:
1. Random drift due to the restricted number of parents;
2. Sampling error in estimating hte generation mean;
3. Variation of selection differentials;
4. Environmental factors.

Sampling variance

$$ \sigma_R^2 = \sigma_d^2 + \sigma_e^2
= V_p(th^2/N_e + 1/M) $$

In the equation, M denotes the of individuals measured.

Selection experiments often yield no response over the first one or two generations, or even longer, but give a clear response later. The reason is usually that the numbers have been too small and random drift in the 'wrong' direction has nullified the response.

c=5
i=1.271
h2=0.3
2*c^2/(i*h2)

Reasons for Asymmetry of Response

1. Random Drift
   to do: simulate the response by considering drift.

2. Inbreeding Depression

3. Genetic Asymmetry
4. Genes with large effect

It is that if the character selected is a component of natural fitness, asymmetry should be expected, with selection towards increased fitness giving a slower response than selection towards decreased fitness.

Long-term Results

yangjl/quantgen documentation built on May 4, 2019, 2:29 p.m.